Examining the driving factors of industrial CO2 emissions in Chinese cities using geographically weighted regression model

The industrial sector is the sector with the largest CO 2 emissions, and to reduce overall CO 2 emissions, analysis of the impact factors holds significance. Based on the 2015 industrial CO 2 emissions of 282 cities in China combined with economic and social data, and a geographically weighted regression (GWR) model, we analysed the characteristics of the spatial distribution of CO 2 emissions and the influencing factors of spatial heterogeneity. The results show that China's urban industrial CO 2 emissions present a significant spatial agglomeration state that includes Shandong, Beijing, Tianjin, Shanghai, Zhejiang, and Jiangsu, and the core of the coastal areas form a high-high (H-H) concentration; a low-low aggregation (L-L) is formed in less developed areas such as Guizhou, Yunnan, Sichuan and Guangxi. The influence of various factors on industrial CO 2 emissions has significant spatial heterogeneity. The Industrial scale, industry share of GDP, and share of the service industry in GDP are factors that promote industrial CO 2 emissions. The technological innovation, population density, and social investment in fixed assets are important factors that inhibit industrial CO 2 emissions, but their impact on industrial CO 2 emissions shows spatial differences. In contrast, the level of economic development, foreign direct investment, financial development and government intervention have a two-way impact on industrial CO 2 emissions.